Hippocampal and amygdalar volume changes in elderly patients with Alzheimer's disease and schizophrenia.

Patients with Alzheimer's disease (AD) and schizophrenia display cognitive, behavioural disturbances and morphological abnormalities. Although these latter reflect progressive neurodegeneration in AD, their significance in schizophrenia is still unclear. We explored the patterns of hippocampal and amygdalar atrophy in those patients and their associations with clinical parameters. Structural magnetic resonance imaging was performed in 20 elderly schizophrenia patients, 20 AD and 19 healthy older controls. Hippocampal and amygdalar volumes were obtained by manual segmentation with a standardized protocol and compared among groups. In both schizophrenia and AD patients, left hippocampal and amygdalar volumes were significantly smaller. The hippocampus/amygdala ratio was significantly lower in schizophrenia compared to both AD cases [2.4 bilaterally, 95% C.I. 2.2 to 2.7] and healthy controls bilaterally [2.5, 95% C.I. 2.3 to 2.9 in left and 2.7, 95% C.I. 2.4 to 3.1 in right hemisphere]. In schizophrenia patients, a significant positive correlation was found between age at disease onset and the right hippocampus/amygdala volume ratio (Spearman rho=0.56). Negative symptoms correlated with higher right/left amygdala volume ratio (Spearman's rho=0.43). Our data show that unlike AD, the hippocampus/amygdala ratio is abnormally low and correlates with the age at onset in schizophrenia, being a neurodevelopmental signature of the disease.

Use of a dynamic foot pressure index to monitor the effects of treatment for equinus gait in children with cerebral palsy.

The purpose of this study is to introduce and describe a newly developed index using foot pressure analysis to quantify the degree of equinus gait in children with cerebral palsy before and after injection with botulinum toxin. Data were captured preinjection and 12 weeks postinjection. Ten children aged 2(1/2) to 6(1/2) years took part (5 boys and 5 girls). Three of them had a diagnosis of spastic diplegia and 7 of congenital hemiplegia. In total, 13 limbs were analyzed. After orientation and segmentation of raw pedobarographic data, we determined a dynamic foot pressure index graded 0 to 100 that quantified the relative degree of heel and forefoot contact during stance. These data were correlated (Pearson correlation) with clinical measurements of dorsiflexion at the ankle (on a slow and fast stretch) and video observation (using the Observational Gait Scale). Pedobarograph data were strongly correlated with both the Observational Gait Scale scores (R = 0.79, P < 0.005) and clinical measurements of dorsiflexion on a fast stretch, which is reflective of spasticity (R = 0.70, P < 0.005). We demonstrated the index's sensitivity in detecting changes in spasticity and good correlation with video observations seems to indicate this technique's potential validity. When manipulated and segmented appropriately, and with the development of a simple ordinal index, we found that foot pressure data provided a useful tool in tracking changes in patients with spastic equinus.

Geographic variation of the greater white-toothed shrew (Crocidura russula Hermann, 1780 Mammalia, Soricidae)

A multivariate morphometric study of the Greater white-toothed shrew (C. russula) throughout its Palearctic range was carried out to search for patterns of geographic variation within the species boundary. Burnaby's and multiple group principal component analysis allowed the adjustment of raw data with respect to within-sample allometric variation. Multivariate 'size-free' results show a stepped dine with the phenotypical trait reduction and shape change from the eastern to the western Maghreb. Pleistocene fossil mandibles proved to have low phenetic distances with eastern populations (Tunisia, east Algeria) and it is argued that their character set is the primitive condition. The ancestral Mid-Pleistocene shrews lived in a relatively more humid climate. Gee-climatic changes in the north African range during the Quaternary provoked phenetic variation of C. russula and, it can be argued, evolution of the modern western C.r. yebalensis. A historical process can thus be assumed as the main cause of this categorical variation, by segmentation of the species range due to gee-climatic events. Morphometric discontinuity within the C. russula Maghreb range is shown to be congruent with karyological and biochemical studies. Moroccan and Tunisian shrews differ, for example, in NFa chromosomes and electrophoretical traits. A stasipatric process should be invoked to explain categorical variation in the Maghreb range. Colonization and divergence of insular populations results in more or less differentiated geographic races. The populations of Ibiza and Pantelleria are close to the species threshold (Nei's D greater than or equal to 0.1). The process of speciation undergone by the Greater white-toothed shrew results in a complex pattern of geographic variation, including both allopatric and non-allopatric modes.

A pipeline approach with spatial information for segmenting multiple sclerosis lesions on brain magnetic resonance imaging

Background: Conventional magnetic resonance imaging (MRI) techniques are highly sensitive to detect multiple sclerosis (MS) plaques, enabling a quantitative assessment of inflammatory activity and lesion load. In quantitative analyses of focal lesions, manual or semi-automated segmentations have been widely used to compute the total number of lesions and the total lesion volume. These techniques, however, are both challenging and time-consuming, being also prone to intra-observer and inter-observer variability.Aim: To develop an automated approach to segment brain tissues and MS lesions from brain MRI images. The goal is to reduce the user interaction and to provide an objective tool that eliminates the inter- and intra-observer variability.Methods: Based on the recent methods developed by Souplet et al. and de Boer et al., we propose a novel pipeline which includes the following steps: bias correction, skull stripping, atlas registration, tissue classification, and lesion segmentation. After the initial pre-processing steps, a MRI scan is automatically segmented into 4 classes: white matter (WM), grey matter (GM), cerebrospinal fluid (CSF) and partial volume. An expectation maximisation method which fits a multivariate Gaussian mixture model to T1-w, T2-w and PD-w images is used for this purpose. Based on the obtained tissue masks and using the estimated GM mean and variance, we apply an intensity threshold to the FLAIR image, which provides the lesion segmentation. With the aim of improving this initial result, spatial information coming from the neighbouring tissue labels is used to refine the final lesion segmentation.Results:The experimental evaluation was performed using real data sets of 1.5T and the corresponding ground truth annotations provided by expert radiologists. The following values were obtained: 64% of true positive (TP) fraction, 80% of false positive (FP) fraction, and an average surface distance of 7.89 mm. The results of our approach were quantitatively compared to our implementations of the works of Souplet et al. and de Boer et al., obtaining higher TP and lower FP values.Conclusion: Promising MS lesion segmentation results have been obtained in terms of TP. However, the high number of FP which is still a well-known problem of all the automated MS lesion segmentation approaches has to be improved in order to use them for the standard clinical practice. Our future work will focus on tackling this issue.

On the tractability of the piecewise-linear approximation for general discrete-choice network revenue management

The choice network revenue management (RM) model incorporates customer purchase behavioras customers purchasing products with certain probabilities that are a function of the offeredassortment of products, and is the appropriate model for airline and hotel network revenuemanagement, dynamic sales of bundles, and dynamic assortment optimization. The underlyingstochastic dynamic program is intractable and even its certainty-equivalence approximation, inthe form of a linear program called Choice Deterministic Linear Program (CDLP) is difficultto solve in most cases. The separation problem for CDLP is NP-complete for MNL with justtwo segments when their consideration sets overlap; the affine approximation of the dynamicprogram is NP-complete for even a single-segment MNL. This is in contrast to the independentclass(perfect-segmentation) case where even the piecewise-linear approximation has been shownto be tractable. In this paper we investigate the piecewise-linear approximation for network RMunder a general discrete-choice model of demand. We show that the gap between the CDLP andthe piecewise-linear bounds is within a factor of at most 2. We then show that the piecewiselinearapproximation is polynomially-time solvable for a fixed consideration set size, bringing itinto the realm of tractability for small consideration sets; small consideration sets are a reasonablemodeling tradeoff in many practical applications. Our solution relies on showing that forany discrete-choice model the separation problem for the linear program of the piecewise-linearapproximation can be solved exactly by a Lagrangian relaxation. We give modeling extensionsand show by numerical experiments the improvements from using piecewise-linear approximationfunctions.

Detection of Raga-characteristic phrases from Hindustani Classical Music Audio

Melodic motifs form essential building blocks in Indian Classical music. The motifs, or key phrases, providestrong cues to the identity of the underlying raga in both Hindustani and Carnatic styles of Indian music. Automatic identification and clustering of similar motifs is relevant in this context. The inherent variations in various instances of a characteristic phrase in a bandish (composition)performance make it challenging to identify similar phrases in a performance. A nyas svara (long note)marks the ending of these phrases. The proposed method does segmentation of phrases through identification ofnyas and computes similarity with the reference characteristic phrase.

The V-ATPase proteolipid cylinder promotes the lipid-mixing stage of SNARE-dependent fusion of yeast vacuoles.

The V-ATPase V(0) sector associates with the peripheral V(1) sector to form a proton pump. V(0) alone has an additional function, facilitating membrane fusion in the endocytic and late exocytic pathways. V(0) contains a hexameric proteolipid cylinder, which might support fusion as proposed in proteinaceous pore models. To test this, we randomly mutagenized proteolipids. We recovered alleles that preserve proton translocation, normal SNARE activation and trans-SNARE pairing but that impair lipid and content mixing. Critical residues were found in all subunits of the proteolipid ring. They concentrate within the bilayer, close to the ring subunit interfaces. The fusion-impairing proteolipid substitutions stabilize the interaction of V(0) with V(1). Deletion of the vacuolar v-SNARE Nyv1 has the same effect, suggesting that both types of mutations similarly alter the conformation of V(0). Also covalent linkage of subunits in the proteolipid cylinder blocks vacuole fusion. We propose that a SNARE-dependent conformational change in V(0) proteolipids might stimulate fusion by creating a hydrophobic crevice that promotes lipid reorientation and formation of a lipidic fusion pore.

Autosomal dominant spondylocarpotarsal synostosis syndrome: phenotypic homogeneity and genetic heterogeneity.

Spondylocarpotarsal synostosis syndrome (SCT) (OMIM 272460), originally thought to be a failure of normal spine segmentation, is characterized by progressive fusion of vertebras and associates unsegmented bars, scoliosis, short stature, carpal and tarsal synostosis. Cleft palate, sensorineural or mixed hearing loss, joint limitation, clinodactyly, and dental enamel hypoplasia are variable manifestations. Twenty-five patients have been reported. Thirteen affected individuals were siblings from six families and four of these families were consanguineous. In four of those families, Krakow et al. [Krakow et al. (2004) Nat Genet 36:405-410] found homozygosity or compound heterozygosity for mutations in the gene encoding FLNB. This confirmed autosomal recessive inheritance of the disorder. We report on two new patients (a mother and her son) representing the first case of autosomal dominant inheritance. These patients met the clinical and radiological criteria for SCT and did not present any features which could exclude this diagnosis. Molecular analysis failed to identify mutations in NOG and FLNB. SCT is therefore, genetically heterogeneous. Both dominant and autosomal recessive forms of inheritance should be considered during genetic counseling.

Landmark detection for fusion of fundus and MRI toward a patient-specific multimodal eye model.

Ophthalmologists typically acquire different image modalities to diagnose eye pathologies. They comprise, e.g., Fundus photography, optical coherence tomography, computed tomography, and magnetic resonance imaging (MRI). Yet, these images are often complementary and do express the same pathologies in a different way. Some pathologies are only visible in a particular modality. Thus, it is beneficial for the ophthalmologist to have these modalities fused into a single patient-specific model. The goal of this paper is a fusion of Fundus photography with segmented MRI volumes. This adds information to MRI that was not visible before like vessels and the macula. This paper contributions include automatic detection of the optic disc, the fovea, the optic axis, and an automatic segmentation of the vitreous humor of the eye.

A structural MRI study of motor conversion disorder: evidence of reduction in thalamic volume.

OBJECTIVE: To investigate potential abnormalities in subcortical brain structures in conversion disorder (CD) compared with controls using a region of interest (ROI) approach. METHODS: Fourteen patients with motor CD were compared with 31 healthy controls using high-resolution MRI scans with an ROI approach focusing on the basal ganglia, thalamus and amygdala. Brain volumes were measured using Freesurfer, a validated segmentation algorithm. RESULTS: Significantly smaller left thalamic volumes were found in patients compared with controls when corrected for intracranial volume. These reductions did not vary with handedness, laterality, duration or severity of symptoms. CONCLUSIONS: These differences may reflect a primary disease process in this area or be secondary effects of the disorder, for example, resulting from limb disuse. Larger, longitudinal structural imaging studies will be required to confirm the findings and explore whether they are primary or secondary to CD.

Phenotypic and molecular characterization of a novel case of dyssegmental dysplasia, Silverman-Handmaker type.

Dyssegmental dysplasia, Silverman-Handmaker type (DDSH; #MIM 224410) is an autosomal recessive form of lethal dwarfism characterized by a defect in segmentation and fusion of vertebral bodies components ("anisospondyly") and by severe limb shortening. It is caused by mutations in the perlecan gene (HSPG2), but so far, only three molecularly confirmed cases have been reported. We report a novel case of DDSH in a fetus that presented at 15 weeks gestation with encephalocele, severe micromelic dwarfism and narrow thorax. After termination of pregnancy, radiographs showed short ribs, short and bent long bones and anisospondyly of two vertebral bodies. The fetus was homozygous for a previously undescribed null mutation in HSPG2.

Hand detection in cluttered scene images using Fourier-Mellin invariant features

This paper proposes an automatic hand detection system that combines the Fourier-Mellin Transform along with other computer vision techniques to achieve hand detection in cluttered scene color images. The proposed system uses the Fourier-Mellin Transform as an invariant feature extractor to perform RST invariant hand detection. In a first stage of the system a simple non-adaptive skin color-based image segmentation and an interest point detector based on corners are used in order to identify regions of interest that contains possible matches. A sliding window algorithm is then used to scan the image at different scales performing the FMT calculations only in the previously detected regions of interest and comparing the extracted FM descriptor of the windows with a hand descriptors database obtained from a train image set. The results of the performed experiments suggest the use of Fourier-Mellin invariant features as a promising approach for automatic hand detection.

Segmentación interactiva multi-clase de personas

La segmentació de persones es molt difícil a causa de la variabilitat de les diferents condicions, com la postura que aquestes adoptin, color del fons, etc. Per realitzar aquesta segmentació existeixen diferents tècniques, que a partir d'una imatge ens retornen un etiquetat indicant els diferents objectes presents a la imatge. El propòsit d'aquest projecte és realitzar una comparativa de les tècniques recents que permeten fer segmentació multietiqueta i que son semiautomàtiques, en termes de segmentació de persones. A partir d'un etiquetatge inicial idèntic per a tots els mètodes utilitzats, s'ha realitzat una anàlisi d'aquests, avaluant els seus resultats sobre unes dades publiques, analitzant 2 punts: el nivell de interacció i l'eficiència.

Hand detection in cluttered scene images using Fourier-Mellin invariant features

This paper proposes an automatic hand detection system that combines the Fourier-Mellin Transform along with other computer vision techniques to achieve hand detection in cluttered scene color images. The proposed system uses the Fourier-Mellin Transform as an invariant feature extractor to perform RST invariant hand detection. In a first stage of the system a simple non-adaptive skin color-based image segmentation and an interest point detector based on corners are used in order to identify regions of interest that contains possible matches. A sliding window algorithm is then used to scan the image at different scales performing the FMT calculations only in the previously detected regions of interest and comparing the extracted FM descriptor of the windows with a hand descriptors database obtained from a train image set. The results of the performed experiments suggest the use of Fourier-Mellin invariant features as a promising approach for automatic hand detection.